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Remote role, common data skillset, and early-career level create moderate applicant competition.
Core data engineering skills are broadly transferable across industries despite optional marketing-domain preference.
Explicit 2–3 years requirement plus mandatory Snowflake, dbt, and Fivetran skills increases filtering strictness.
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Build, maintain, and optimize scalable ELT data pipelines and data transformation models using Snowflake, dbt, and Fivetran.
Design and optimize data warehouse solutions focusing on performance, scalability, and cost efficiency.
Collaborate with business and technical teams to integrate multi-source data, ensure data quality, and support analytics and reporting initiatives.
2–3 years of experience specifically in Data Engineering or Analytics Engineering.
Bachelor's degree in Computer Science, IT, Engineering, or related field.
Hands-on experience with Snowflake, dbt, Fivetran, SQL development, and Python scripting.
Experience with data modeling (dimensional/star schema), cloud platforms (AWS, Azure, or GCP), Agile development, CI/CD for data workflows, and API integrations with semi-structured data.
Operationally experienced with modern data engineering tools and ELT frameworks in a cloud environment.
Familiar with handling complex data domains such as media, digital marketing, or programmatic advertising data or similar.
Capable of working cross-functionally to translate business requirements into reliable, business-ready datasets with strong emphasis on data quality and pipeline optimization.